Minimum Consumption Research Articles

An investigation of the surface topography of wire tool and the modelling of wire electro-spark machined ti-alloy using ANN

Abstract Titanium and its alloys are in demand in the field of biomedical and aerospace engineering because of its high strength-to-weight ratio and anti-corrosive properties. WESM emerged as a processing method as traditional methods could not process because of strain hardening and low material conductivity; however, wire tool consumption contributes to high costs while processing with WESM. The current Article investigates the effect of input factors on wire consumption and their significance level on wire consumption. A total of 81 experimental runs were conducted while taking input factors Spark on, Spark off time, peak current and servo voltage at three levels, each using a full factorial approach. Experimental results were analysed using ANOVA and MLR (Multi-Linear regression). Moreover, ANN modelling is done to model the wire consumption using a 4-10-1 architecture that increased the coefficient of correlation (R2) up to 0.991. Lastly, after processing, the wire tool surface is evaluated using a scanning electron microscope to assess the effect of various input energy levels and find input combinations for minimum wire consumption

A Systematic Review on Drug-to-Drug Interaction Prediction and Cryptographic Mechanism for Secure Drug Discovery Using AI Techniques

Recently, poly-pharmacy persistence has greatly improved in treating multiple diseases effectively. However, determining potential drug–drug interaction (DDIs) during the drug design is critical for controlling the target clinical drug during secure testing. In the medical field, DDIs are significant for disease diagnosis and treatment, mainly aiding researchers in predicting the link between biomolecules for efficient drug discovery (DD). Artificial intelligence (AI) has recently witnessed researchers accurately predict DDIs at minimum time consumption. Although the AI models show accurate results by aiding physicians to determine poly-pharmacy, several unresolvable issues remain in promoting reliability due to high error, complexity and cost-effectiveness. This paper aims to provide a comprehensive review using AI techniques (machine learning (ML)–deep learning (DL) models) and security enhancement techniques to improve DDI prediction and DD, respectively. The recent state of DDI prediction and the security concerns are presented initially, along with a short discussion about the need for effective techniques. Then, the critical evaluation related to existing studies is analyzed and compared to current issues faced in those existing studies. Various pharmaceutical drugs and their pros are also surveyed in addition to the security analysis for the newly invented drugs. Several assessment measures for the surveyed techniques are also conquered and put forth the need for advancements in future techniques effectively. The performance variations produced by the existing studies are also surveyed, and their use in the medical industry is also provided in this review study. The review of this research encourages the researchers to analyze the various issues faced in the pharmaceutical industry so that a novel technique can be introduced in the upcoming studies.

Digital twin for decision support system of industrial utility management

Manufacturing and industrial operations rely heavily on energy that is generated mostly from fossil fuels, such as coal, oil, and natural gas, which harm the environment and contribute to climate change. Thus, renewable energy is being integrated into industrial processes to lessen environmental effects and reduce fossil fuel usage. However, the renewable source performance process can be greatly affected by disturbances and constraints, such as ambient air temperature and relative humidity, minimum utility consumption, and the total energy required, making effective control difficult. This study proposes a digital twin built with machine learning regression techniques for load demand forecasting as a decision-support system for industrial utility management. From the results, the ensemble tree (ET) model produced the highest accuracy, based on validation and test dataset root mean squared error values of 23.164 and 27.558, respectively, and R2 values of 0.96 and 0.95, respectively. The digital twin and load demand forecasting approaches effectively created an efficient operating schedule for industrial utility management. The ET model had a total error of 23.86%, substantially lower than the average load demand's total error of 65.29%. Therefore, the ET model with weather conditions in four scenarios could be recommended to optimize energy utilization when creating the operating schedule.

Comparative analysis of powertrain architectures for fuel cell light commercial vehicles in terms of performance and durability

At the present time, the critical climate situation has raised awareness about the importance of developing carbon-free technologies. In this context, fuel cell systems (FCS) have become one of the key technologies in the pathway to decarbonization. Given that road transport is a major contributor to greenhouse gas (GHG) emissions, this paper focuses on a specific segment of this sector: light commercial vehicles (LCVs). The current market situation shows that LCV manufacturers have not yet decided what is the appropriate powertrain architecture for this kind of vehicle. Thus, the current paper studies a wide range of possible FCS-based propulsive system designs, changing the size of the FCS, electric battery and H2 tank. These propulsive system architectures are analyzed concerning the performance of the vehicle, in terms of consumption and range, and the durability of its FCS. The evaluation of these different designs will be highly valuable for the LCV industry and manufacturers, as it allows to understand the optimal powertrain solution. The study demonstrates that a significant increase in range can be achieved with only a minor penalty in hydrogen consumption. Additionally, the research indicates that it is feasible to employ one of the most durable FCS designs while meeting LCV mission requirements with minimal consumption penalty. In conclusion, this paper provides valuable data to the ongoing research in this field, offering a detailed analysis of the impact of H2 consumption, autonomy, and durability of the FCS across various vehicle architectures under typical LCV driving conditions.

Adaptive control of plug-in hybrid electric vehicles based on energy management strategy and dynamic programming algorithm

This study mainly analyses the fuel consumption of plug-in hybrid vehicles during operation. A new control method for automobiles based on energy management strategy and dynamic programming algorithm is proposed. The new method plans and analyses the minimum electricity consumption, and then uses dynamic programming algorithms to analyse this parameter. The research results indicated that the vehicle state was constantly changing with the variation of SOC value during driving. The energy mobilization of the vehicle was more obvious after adding dynamic programming strategy. The efficiency of the vehicle was relatively high in driving state 1, with a minimum value of 70%, which was about 20% higher than in driving state 4. The average fuel consumption in driving state 2 was 1.8L higher than in other driving states. The overall efficiency of automobiles after incorporating dynamic programming was improved, with a shorter time to reach the lowest efficiency point compared with not incorporating dynamic programming algorithms. The highest efficiency value was 7.86% higher than that of not incorporating dynamic programming models. The new control method can reduce energy consumption and improve the energy management and control effect. The study provides a better research direction for energy management and control of hybrid electric vehicles in the future.

The Impact of Tea Consumption on Cardiovascular Health

Tea is a popular beverage that comprises various antioxidants. Tea is the second most consumed beverage in the world after water. The three ideal types of tea include black, white, and green teas. Catechin, Epicatechin gallate, and Epicatechin are the striped flavonoids coeval in the tea. These flavonoids are freed as a rich source for blood circulation in the heart. Tea possesses antiinflammatory, anti-neoplastic, anti-arthritic, anti-thrombotic, antimicrobial, anti-platelet aggregation, anti-cholesterol, anti-hyperglycemic, and immuno-protective properties. Modern empowering research studies contemplate that minimal consumption of tea can also be of advantage to the cardiovascular system (CVS) as it modulates oxidative stress. Consumption of tea is beneficial for cardiovascular diseases such as atherosclerosis, coronary artery disease, aortic aneurysms, peripheral artery disease, stroke, ischemic heart disease, and cardiomyopathy. Consumption of excess tea may also be detrimental to health, and we highlight different types of tea. The main aim of the present narrative review is to highlight the natural compounds present in tea and discuss their mechanism of action on the cardiovascular system. Based on evidence gathered from published literature, it is thereby concluded that tea is a popular drink with potential cardiovascular health benefits.

Traditional and contemporary building thermal sensations prediction models in a warm-humid climate

ABSTRACT Passive ways of providing thermal comfort have been intensively researched in many nations. Despite researchers’ strenuous efforts, most studies on thermal comfort concerns are centred on continents such as Asia, America, Europe, and Africa, with a handful of studies comparing building types in the sub-Saharan area. However, none has focused on statistical models to predict the thermal sensations of occupants in traditional and modern structures during the dry season. Hence, this study investigated interior relative humidity, air temperature, and occupants’ thermal feelings in traditional and modern structures in the dry season in Okigwe, Nigeria. The data for this investigation was collected by physically measuring relative humidity and air temperature using data loggers. A longitudinal survey technique was also used to elicit answers from the residents of the selected traditional and modern structures on the thermal feeling of comfort temperature. To predict the inhabitants’ thermal sensations in the building types investigated, two statistical models were developed: ‘TSVt = 0.65 (MITt) – 13.5’ for traditional structures and ‘TSVc = 0.74 (MITc) – 16’ for modern. The comfort range and neutral temperature of ‘3.15 ≤ TSV ≤ 4.85’ 1–7 yielded 26.8°C as the neutral temperature for the occupants of traditional buildings, with the comfort ranging between 25.6°C and 28.2°C. Contemporary building occupants’ neutral temperature and comfort ranges from 25.9°C to 28.2°C. The study therefore recommended the use of the developed models by Architects, Planners, and Designers for predicting the occupants’ sensations of the building types before preliminary investigations and design sketches, as with such information, the designer possesses the necessary tools for providing buildings that are thermally comfortable for maximum comfort and minimal consumption of energy.

Exploring residential minimum night consumption in a real water distribution network based on smart-meter data

An accurate estimation of leakages in water distribution networks is of primary importance for the definition of strategies aimed at ensuring an efficient management of water resources and avoiding water waste. However, in the case of methods based on water balance—such as the Minimum Night Flow method—inaccurate assessment of the minimum night consumption (MNC), e.g. the assumption of fixed MNC values from the literature, can heavily mislead the quantification of leakage level. This study aims at providing insights into the variability of MNC and the related drivers. In greater detail, hourly water consumption data of approximately 200 users are collected over a period of two years and subjected to a multi-phase methodology to obtain a detailed characterization of MNC, with and without considering the users affected by post-meter leakages. The study demonstrates that factors such as seasonality or the presence of post-meter leakages may strongly impact the MNC—the values of which can significantly deviate from the literature references—and thus lead to significant misestimation of network leakages in water systems.Graphical

On-Demand Coalescence of Ferromagnetic Droplets in Microchannels Using an Oscillating Magnetic Field.

Droplet-based microfluidics exhibit remarkable potential in achieving high-throughput chemical reactions with minimal reagent consumption. However, a pivotal challenge lies in the selective coalescence of droplets for precise process control, particularly when dealing with droplets of varying amounts and volumes, which are difficult to trap and coalesce due to their tiny dimensions and incessant movement. Hence, we proposed a method for on-demand coalescence of ferromagnetic droplets using an oscillating magnetic field. Experimental results show that the ferromagnetic droplets can be trapped in different positions in the microchannels according to the applied magnetic field intensity. A high-intensity pulsed amplitude of the magnetic field enables the migration of trapped droplets toward the same position, facilitating their mutual contact and interaction. By programmable modulation of the oscillating magnetic field, a controllable reciprocation of droplets in microchannels was successfully realized, which enabled us to dynamically capture, coalesce, and release two or more (≥3) droplets on demand. The integrated ferromagnetic droplet-based microfluidic platform allows contact-free, easily monitored, and on-demand coalescence of ferromagnetic droplets in microchannels, which holds promise for a wide range of applications, such as microfluidic-based drug synthesis, biosensing, reaction kinetics, and paracrine signaling, particularly.

Impact of smokeless tobacco on psychological and oxidative stress in unemployed indian youth

In India, tobacco (nicotine) addiction among youth has increased, leading to substantial socioeconomic burdens, mortality, and morbidity. While minimal short-term nicotine consumption may have antioxidant effects, chronic exposure results in various adverse health outcomes. This study examines the impact of chronic nicotine consumption on cellular oxidative stress and psychological stress, and their correlation with Homocysteine (Hcy) levels in unemployed tobacco consumers. This case-control study included 156 healthy, educated, unemployed male volunteers aged 20–40 years, divided into nicotine-addicted (n = 80) and non-addicted (n = 76) groups. Psychological stress was assessed using perceived stress scales (PSS) and coping self-efficacy (CSE) scales. Oxidative stress markers, including Malondialdehyde (MDA), Superoxide Dismutase (SOD), and Catalase, were measured. Hcy levels were quantified using high-performance liquid chromatography (HPLC). Nicotine-addicted participants exhibited significantly higher perceived stress (p = 0.0001) and lower coping self-efficacy (p = 0.0001) compared to non-addicted individuals. MDA levels in erythrocytes were significantly increased (p = 0.0006), while SOD (p = 0.0001) and Catalase (p = 0.02) activities were significantly decreased in the addicted group. Nicotine intake influenced Hcy concentrations, with 55% of addicted individuals falling into moderate, 27.5% into intermediate, and 7.5% into severe Hcy categories. Chronic nicotine intake also reflected the hematological parameters (WBCs, RBCs, HGB, and Platelets). Chronic tobacco consumption induces oxidative stress and perceived psychological stress, leading to elevated Hcy levels in nicotine consumers. The study highlights the detrimental effects of nicotine addiction on cellular defensive mechanisms, emphasizing the need for targeted interventions to address this growing health issue among unemployed Indian youth.

Environmentally friendly screen-printed electrodes for the selective detection of 4-bromo-2,5-dimethoxyphenethylamine (2C-B) in forensic analysis.

In response to the growing need for sustainable analytical methods, this study explores the repurposing of screen-printed electrodes (SPEs) that would otherwise be discarded. This involves recoating the working electrode surface with a graphite (Gr) and chitosan (CTS) dispersion, creating a reusable SPE (SPE-Gr/CTS). Demonstrating its utility, SPE-Gr/CTS was employed for the detection of 4-bromo-2,5-dimethoxyphenethylamine (2C-B), a phenylethylamine commonly used for recreational proposes. Identifying 2C-B in fluid oral and seized samples is of great interest for forensic and toxicological applications. The 2C-B detection using SPE-Gr/CTS was optimized in Britton-Robinson buffer solution (0.1 mol L-1) at pH 2.0, employing square-wave adsorptive stripping voltammetry. The electrochemical behavior of 2C-B on SPE-Gr/CTS exhibited one irreversible oxidation and a reversible redox process. The proposed method presented a dynamic linear range for 2C-B determination (0.05 to 7.5 μmol L-1) with a low LOD (0.015 μmol L-1). Moreover, the stability of 2C-B electrochemical responses on SPE-Gr/CTS was confirmed using the same or different electrodes (N = 3), with a relative standard deviation of less than 5.0%. Interference studies with seventeen other illicit drugs and adulterants demonstrated that the proposed method is selective for 2C-B detection even in the presence of these substances. Real seized and oral fluid samples containing 2C-B were analyzed using this method, and the results were confirmed by LC-MS. The proposed device demonstrates to be an environmentally friendly and selective sensor for 2C-B detection in forensic analysis, offering a rapid and straightforward screening method for seized and biological samples. In addition, a portable and sensitive determination of 2C-B in forensic samples is presented with minimal sample consumption (50 μL).

Assessing Water Demands and Allocation Strategies Using the Water Evaluation and Planning System—A Case Study of the Ghrib Basin, Algeria

The Ghrib Basin is currently encountering water-related challenges due to population growth and growing competition among water users. Therefore, assessing the current water situation is essential for the anticipation of future needs in the region. This paper assesses water demand and allocation strategies in the Ghrib Basin, Algeria, using the Water Evaluation and Planning (WEAP) system. The simulation is based on five scenarios: “Increase in population and agricultural activity”, “Improving agricultural activity”, “Minimum domestic consumption”, “Enhancing Water Resources”, and “Best practice”, (which is a combination of two scenarios, i.e., “Improving agricultural activity” and ”Minimum domestic consumption”). The simulation outcomes indicate that the “Best practice” scenario represents the most advantageous and beneficial scenario by which the problem of the unmet demand can be solved. The resulting simulations indicated the need for the employment of water-efficient irrigation systems as well as the encouragement of sustainable water use, such as drip irrigation, which necessitates coordinated efforts and particular infrastructural investments. The derived outcomes are highly convincing and have the potential to serve as a decision support system for the effective governance of water resources in the Ghrib Basin. The methodology utilized in this study has the potential to be implemented in any basin across the globe.

A lightweight visual mamba network for image recognition under resource-limited environments

The Vision Transformers (ViTs) models show great potential in recognition due to their excellent self-attention mechanisms. However, they often need more computational complexity, making achieving high performance in resource-constrained environments challenging. This paper proposes a lightweight visual model (called LightViM) to tackle these challenges, specifically devised for recognition challenges under resource-constrained environments. Considering the imperative of reducing the model’s computational complexity and resource consumption , we propose lightweight local–global feature fusion modules based on Mamba (LGF-Mamba) aimed at integrating spatially detailed local information with globally contextualized features while maintaining lower linear time complexity. In LGF-Mamba, Mamba sub-blocks are first designed to extract global information; then, for the rapid extraction of local features, LocalE module is designed and integrated into LGF-Mamba, exploring more comprehensive feature representation. This mechanism efficiently directs the network to integrate features from different spatial scales, thereby improving the recognition performance in resource-constrained environments. Experimental results indicate that, in comparison to other leading-edge lightweight methods, the proposed procedure simultaneously achieves superior recognition performance and minimal resource consumption.

Impact of Self-Assembled Monolayer Structural Design on Perovskite Phase Regulation, Hole-Selective Contact, and Energy Loss in Inverted Perovskite Solar Cells

Recent studies have shown that self-assembled molecule (SAM)-based hole-selective contacts (HSCs) offer a promising solution to the challenges faced by perovskite solar cells (PVSCs), including minimal material consumption, scalable production, high interface stability, and the use of environmentally friendly solvents. In this study, the efficacy of two designs of SAMs (Cz and PA) as HSCs in inverted PVSCs was investigated by comparing them with the conventional MeO-2PACz (MeO) SAM. Surface analyses showed that the surface of PA is smoother than that of Cz, which helps to reduce interfacial defects. Subsequent perovskite deposition exhibited a reduced formation of the PbI2 phase, incidiating that its phase modulation ability is superior to that of MeO. Further analyses demonstrate the superior charge extraction ability of PA as a result of reduced interfacial defects and non-radiative recombination at the HSC/perovskite interface. By further coupling with phenethylammonium iodide (PEAI) surface passivation, both interfaces of the perovskite film were optimized and the inverted ((FAPbI3)0.85(MAPbBr3)0.15)0.95(CsPbI3)0.05 (bandgap = 1.62eV) PVSC achieves a high power conversion efficiency (PCE) of 23.3% and a very high open-circuit voltage of 1.227V due to the largely reduced energy loss. In addition, the PA PVSC exhibits enhanced long-term thermal stability at 85°C in a nitrogen atmosphere.

РОЛЬ САСО3 У ФОРМУВАННІ МІЦНІСНИХ І ДЕКОРАТИВНИХ ВЛАСТИВОСТЕЙ ПОРОШКОВОГО ЛУЖНО-АКТИВОВАНОГО ШЛАКОПОРТЛАНДЦЕМЕНТНОГО БЕТОНУ

The article discusses approaches to the formation of compositions of alkali-activated decorative Portland slag cements containing Portland cement type CEM1 5...45% with high performance and decorative properties. The optimization of the compositions of decorative alkali-activated Portland slag cements was carried out using statistical methods for designing experiments. Finely dispersed TiO2 and CaCO3 additives with a whiteness of 90% were used as bleaching components. The alkaline component is sodium metasilicate in the form of a non-hygroscopic powder. The research carried out made it possible to obtain decorative Portland slag cements with a whiteness of 45...77%, which allows them to be used to produce colored cements with a wide range of colors from white to black. It has been established that alkali-active decorative Portland slag cements have an activity of 37...59 MPa at the age of 28 days. All compositions have good hardening dynamics and, based on the strength at the age of 2 days  22...36.6 MPa, they can be classified as fast-hardening. Based on them, it is possible to produce dry construction mixtures. All mortar compositions based on alkali-active decorative Portland slag cements demonstrate fairly high frost resistance  F200. This allows them to be used for the manufacture of products and solutions both for indoor use and when exposed to atmospheric influences without loss of design characteristics and decorative appeal. The inherent shrinkage strains of decorative alkali-activated Portland slag cements are 0.51...0.61 mm/m, which eliminates cracking and premature destruction of products. The use of the CaCO3 additive is especially effective for controlling the shrinkage deformations. Thus, the CaCO3 additive performs the functions of not only a decorative component, but also a structure-forming component. Concrete and mortar mixtures can be used to produce decorative products using the traditional method, extrusion, 3D printing on construction printers, etc. And not too long setting times and a rapid increase in strength make it possible to produce products without thermal treatment or with minimal consumption of thermal energy.

Atomically Permeated MoP‐WOx Core‐Shell Catalysts for Efficient and Selective Oxidation of Thiophenic Sulfides in Fuels via Direct Electron Transfer Mechanism

AbstractHeterogeneous interfaces designed rationally in catalysts can induce geometrical, compositional, and electronic effects that can be applied to modulate catalytically active sites and consequently accelerate reaction kinetics. Here, a core‐shell heterostructure catalyst consisting of crystalline molybdenum phosphide (MoP) cores and amorphous tungsten oxide (WOx) shells on porous carbon nanosheets (PCN) is developed for oxidative desulfurization (ODS) of fuels. The strongly coupled core‐shell heterogeneous interface triggers a distinctive atomic permeation effect that induces substantial electron transfer from MoP to WOx and subsequent generation of electron‐rich W sites, consequently optimizing the adsorption of intermediates and substrates. The resulting catalyst (WOx@MoP/PCN) demonstrates a turnover frequency as high as 768.1 h−1 for ODS at 60 °C, exceeding that of almost all the state‐of‐the‐art ODS catalysts by 1–2 orders of magnitude. Moreover, a novel surface oxidation pathway based on direct electron transfer is identified in the WOx@MoP/PCN‐H2O2 system, which bypasses the formation of reactive oxygen species, consequently endowing the system with a moderate redox potential. Thus, WOx@MoP/PCN exhibits unprecedented selectivity, achieving 100% removal of thiophenic sulfides from real diesel with minimal consumption of oxidant.

Innovative Trends in Modified Membranes: A Mini Review of Applications and Challenges in the Food Sector.

Membrane technologies play a pivotal role in various industrial sectors, including food processing. Membranes act as barriers, selectively allowing the passage of one or other types of species. The separation processes that involve them offer advantages such as continuity, energy efficiency, compactness of devices, operational simplicity, and minimal consumption of chemical reagents. The efficiency of membrane separation depends on various factors, such as morphology, composition, and process parameters. Fouling, a significant limitation in membrane processes, leads to a decline in performance over time. Anti-fouling strategies involve adjustments to process parameters or direct modifications to the membrane, aiming to enhance efficiency. Recent research has focused on mitigating fouling, particularly in the food industry, where complex organic streams pose challenges. Membrane processes address consumer demands for natural and healthy products, contributing to new formulations with antioxidant properties. These trends align with environmental concerns, emphasizing sustainable practices. Despite numerous works on membrane modification, a research gap exists, especially with regard to the application of modified membranes in the food industry. This review aims to systematize information on modified membranes, providing insights into their practical application. This comprehensive overview covers membrane modification methods, fouling mechanisms, and distinct applications in the food sector. This study highlights the potential of modified membranes for specific tasks in the food industry and encourages further research in this promising field.

Increasing photovoltaic self-consumption for objects using domestic hot water systems

The technique of estimating the expected decrease in electricity consumption from the grid and using PV energy for the taken load schedule based on archival data for 5 years is refined. With full self-consumption (SC), the reduction of consumption from the grid can be increased by 9.5%–30.7% for a year according to the rated PV power. Consumption should increase when PV generation exceeds a certain value. A discrete time control of the power of an electric storage boiler (ESB) is proposed based on the deviation of the storage battery (SB) state of charge from a given schedule with a heating concentration during hours of high PV generation. In the considered application, it is possible to increase SC by up to 21%. Reducing the load in the evening allows us to use SB energy to reduce consumption from the grid at night. The possibility of complete photovoltaic SC when the ESB is used with an air conditioner is substantiated. Limitations for air conditioner energy consumption according to PV generation are determined. The system’s 24h model of energy processes is supplemented with a thermal model. The standard use of ESB with water temperature maintenance was also considered for comparison. ESB power control allows you to reduce daily energy consumption from the grid by 1.7–2 times. When combining an adjustable ESB with an air conditioner, it is possible to reduce consumption from the grid by 1.466–1.558 times at minimum and increase consumption from the grid by 2–5% at maximum air conditioner consumption.

Characterizing biomolecular structure features through an innovative elliptical dichroism spectrometry for cancer detection

This research introduces a novel method for evaluating the structural features of biomolecules, utilizing our innovative Elliptical Dichroism (ED) spectrometer specifically designed for stereochemical analysis. By integrating ED spectrometry with autocorrelation (AC) analysis, we investigate the conformational characteristics of biological molecules such as amino acids, proteins, and extracellular vesicles (EVs) induced by elliptically polarized UV absorption. Our streamlined approach offers a cost-effective and portable solution with minimal sample consumption and supports multiple working modes to efficiently characterize biomolecular structures. The insight from this new approach demonstrates potential applications in using biomolecular characterization for cancer detection.

Control of properties of core mixes manufactured by Cold‑box‑amineprocess

The article considers the strength issues of foundry cores manufactured by the Cold‑box‑amine process. It is shown that the properties of the core mix can be controlled by adjusting the formulation. Examples of the influence of binders’ consumption on the properties of the mixes are given: a decrease in resin and polyisocyanate leads to a decrease in strength and a decrease in life. In addition, the minimum consumption of binders varies from manufacturer to manufacturer. Recipes of mixes with special additives are given, which allow, by reducing the strength of the mix, to ensure the completeness of the polymerization reaction.